class_docstr: ```
  predictions for tabular data
  ```
code: def _predict_shap(self, X):
      n_cats = len(self.preproc.cat_names)
      n_conts = len(self.preproc.cont_names)
  
      # reformat for model
      batch_x = [X[:, i : i + 1] for i in range(n_cats)] + [
          X[:, -n_conts:]
      ]
      result = self.model.predict(batch_x)
      return result
  
file_path: ktrain/ktrain/tabular/predictor.py
imports: from ..None import utils
  from ..imports import *
  from ..predictor import Predictor
  from .preprocessor import TabularPreprocessor
label_desc: Use image node_id 4 for calling the TabularPredictor obj's underlying member method code with example usage: obj._predict_shap(X) and returns: result